In Stochastic Gradient Descent, the term "stochastic" refers to the fact that the algorithm uses a __________ subset of data to perform an update.

In Stochastic Gradient Descent, each update is noisier than in batch gradient descent, which can be a , but can also help escape .

Stochastic gradient descent has fewer amount of computation per gradient update than standard gradient descent.*TrueFalse

1. Mention the advantages of Stochastic gradient descent.

Under which situations will you prefer to go for "Stochastic gradient descent" and give recommendations accordingly?Select an option Clear ResponseCalculations are done in such a way that the training data instance and its updates are calculated immediately.Calculations are done in such a way that the training data instance and its updates are calculated as a batch process.Calculations are done in such a way that the training data instance and its updates are calculated every day at a particular time.Calculations are done in such a way that the training data instance is calculated immediately, but its updates will happen in a batch.

What is correct about stochastic gradient descent? (select all that apply)1 pointThe loss may exhibit sudden increases The loss must be linearIt's an approximation of batch gradient descent